Generally, MIMO systems employing multiple transmit/receive antennas, which are radio transmission systems that can maximize data transmission rate through spatial multiplexing together with diversity gain, are established as the core technology of the next generation mobile communications. But, this improvement of reliability and performance causes an increase of complexity of hardware and also an increase of cost due to use of a plurality of Radio Frequency (RF) chains.
On the other hand, when comparing a system that uses N RF chains and N antennas with a system that selects and uses N antennas among M (M≧N) while adopting the same N RF chains, the latter system using antenna selection leads to a very large improvement of performance although using the same number of RF chains. Therefore, there has been considered an antenna selection technique as a scheme that takes advantages of MIMO systems while lowering complexity of system hardware and decreasing cost owing to use of plural RF chains.
Meanwhile, as prior arts for adopting an antenna selection technique at both transmitting and receiving ends, there are “Full Exhaustive Search” (Andreas F. Molish, M. Z. Win and J. H. Winters), and “Capacity of MIMO Systems with Antenna Selection”, Communications, IEEE Int'l Conf., vol. 2, pp. 570-574, June 2001, which calculate given capacitances of all possible subsets of antennas and then decide a subset with the maximum capacitance. Also, there are further proposed “Partial Exhaustive Search” (A. Gorohkov, M. Collados, D. Gore and A. Paulraj), and “Transmit/Receive MIMO Antenna Subset Selection”, Acoustics, Speech, and Signal Processing, Proceedings, ICASSP, IEEE Int'l Conf., vol. 2, pp. ii-13-16, May 2004. These prior arts derive determinants of all cases with size of MR×MT through exhaustive search and select a subset with the maximum capacitance among them at a transmitting end, rather than finding a required subset at a time; and then find LR×LT from MR×MT through exhaustive search for a selected antenna at a receiving end.
However, since these conventional methods are all based on the exhaustive search, they have a very large unreal complexity. In other words, the full exhaustive search calculates determinants of all cases by searching by the number of cases of
            (                                                  M              R                                                                          L              R                                          )        ⁢          (                                                  M              T                                                                          L              T                                          )        ,thereby resulting in a very much amount of calculation and a very high degree of complexity. Meanwhile, the partial exhaustive search conducts searching by the number of cases of
            (                                                  M              R                                                                          L              R                                          )        +          (                                                  M              T                                                                          L              T                                          )        ,which brings about a large reduction of an amount of calculation. However, this search still requires calculation of a great number of determinants, thus leading to a very high degree of complexity.